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» Efficient Piecewise Learning for Conditional Random Fields
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JMLR
2012
13 years 2 months ago
Sample Complexity of Composite Likelihood
We present the first PAC bounds for learning parameters of Conditional Random Fields [12] with general structures over discrete and real-valued variables. Our bounds apply to com...
Joseph K. Bradley, Carlos Guestrin
PAMI
2008
119views more  PAMI 2008»
14 years 11 months ago
Triplet Markov Fields for the Classification of Complex Structure Data
We address the issue of classifying complex data. We focus on three main sources of complexity, namely, the high dimensionality of the observed data, the dependencies between these...
Juliette Blanchet, Florence Forbes
IJCV
2006
236views more  IJCV 2006»
14 years 11 months ago
A Feature-based Approach for Dense Segmentation and Estimation of Large Disparity Motion
We present a novel framework for motion segmentation that combines the concepts of layer-based methods and feature-based motion estimation. We estimate the initial correspondences...
Josh Wills, Sameer Agarwal, Serge Belongie
ECCV
2006
Springer
16 years 1 months ago
Statistical Priors for Efficient Combinatorial Optimization Via Graph Cuts
Abstract. Bayesian inference provides a powerful framework to optimally integrate statistically learned prior knowledge into numerous computer vision algorithms. While the Bayesian...
Daniel Cremers, Leo Grady
TIST
2011
136views more  TIST 2011»
14 years 6 months ago
Probabilistic models for concurrent chatting activity recognition
Recognition of chatting activities in social interactions is useful for constructing human social networks. However, the existence of multiple people involved in multiple dialogue...
Jane Yung-jen Hsu, Chia-chun Lian, Wan-rong Jih